release: v0.4.1 — code quality fixes and doc updates

Remove unsafe `as any` casts, fix MetricsPage fetch cancellation safety,
delete dead AppBarGpuBadge component, fix typo in data context, move
extractJsonData to module scope, resolve ESLint/Prettier indent conflict,
fix artifacthub-pkg.yml version mismatch and inaccurate description.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
DevContainer User
2026-03-04 13:05:58 +00:00
parent e451e3906e
commit 1ae6e2d355
8 changed files with 75 additions and 110 deletions
+5
View File
@@ -1,3 +1,8 @@
module.exports = {
extends: ['@headlamp-k8s/eslint-config'],
rules: {
// Prettier handles indentation; the shared config's indent rule
// conflicts with Prettier's JSX ternary formatting.
indent: 'off',
},
};
+2 -2
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@@ -35,7 +35,7 @@ src/
├── index.tsx # Plugin entry: registerRoute, registerSidebarEntry, registerDetailsViewSection, registerResourceTableColumnsProcessor
├── api/
│ ├── k8s.ts # Types + helpers (GpuDevicePlugin CRD, Nodes, Pods, type guards, formatters)
│ ├── k8s.test.ts # Tests for k8s helpers (70+ test cases)
│ ├── k8s.test.ts # Tests for k8s helpers (48 test cases)
│ ├── metrics.ts # Prometheus GPU power metrics (node-exporter i915 hwmon)
│ └── IntelGpuDataContext.tsx # Shared React context provider with data fetching
└── components/
@@ -44,7 +44,7 @@ src/
├── NodesPage.tsx # Per-node GPU type, device count, allocation, workload pods
├── PodsPage.tsx # All pods requesting Intel GPU resources with per-container detail
├── MetricsPage.tsx # Real-time GPU power metrics from Prometheus
├── NodeDetailSection.tsx # Injected into native Node detail page (capacity, utilization, pods)
├── NodeDetailSection.tsx # Injected into native Node detail page (capacity, utilization, pods)
├── PodDetailSection.tsx # Injected into native Pod detail page (GPU requests per container)
└── integrations/
└── NodeColumns.tsx # GPU Type and GPU Devices columns for native Nodes table
+18 -28
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@@ -1,4 +1,4 @@
version: "0.4.0"
version: "0.4.1"
name: intel-gpu
displayName: Intel GPU
description: >-
@@ -8,14 +8,14 @@ description: >-
sections into native Node and Pod detail pages. Supports discrete (i915),
Xe, and integrated GPU nodes with graceful degradation when the device
plugin operator is not installed. Includes a Metrics page showing real-time
engine utilization, GPU frequency, VRAM usage, and energy from the device
plugin's Prometheus endpoint.
GPU power draw and TDP from node-exporter i915 hwmon metrics (discrete GPU
nodes only).
createdAt: "2026-02-18T00:00:00Z"
license: Apache-2.0
category: monitoring-logging
homeURL: https://github.com/privilegedescalation/headlamp-intel-gpu-plugin
appVersion: "0.3.0"
appVersion: "0.4.0"
keywords:
- headlamp
@@ -45,33 +45,23 @@ links:
url: https://intel.github.io/intel-device-plugins-for-kubernetes/
changes:
- kind: added
description: "Metrics page: document which metrics require what infrastructure (power via hwmon works out of the box; frequency and utilization need custom exporters)"
- kind: added
description: "Metrics page: real-time GPU power draw (W) and TDP via node-exporter i915 hwmon metrics in kube-prometheus-stack"
- kind: fixed
description: "Remove unsafe `as any` casts in NodeDetailSection"
- kind: fixed
description: "Fix MetricsPage fetch cancellation safety (prevent setState on unmounted component)"
- kind: fixed
description: "Fix typo gpuPluinPods → gpuPluginPods in data context"
- kind: changed
description: "Sidebar label changed to intel-gpu"
description: "Move extractJsonData utility to module scope to avoid recreation on every render"
- kind: removed
description: "Removed app bar health badge"
- kind: added
description: "Overview dashboard: plugin health, GPU node summary, allocation bar, active GPU pods"
- kind: added
description: "Device Plugins page: GpuDevicePlugin CRD instances with spec/status and daemon pods"
- kind: added
description: "GPU Nodes page: per-node GPU type, device count, allocation, workload pods"
- kind: added
description: "GPU Pods page: all pods requesting Intel GPU resources with per-container detail"
- kind: added
description: "Node detail injection: Intel GPU section on native Node detail pages (capacity, allocatable, utilization, active pods)"
- kind: added
description: "Pod detail injection: GPU resource requests/limits per container on native Pod detail pages"
- kind: added
description: "Nodes table: GPU Type and GPU Devices columns injected into native Nodes table"
- kind: added
description: "App bar health badge: hidden when no Intel GPU plugin detected"
description: "Remove dead AppBarGpuBadge component"
- kind: fixed
description: "Fix appVersion mismatch and inaccurate metrics description in Artifact Hub metadata"
- kind: fixed
description: "Resolve ESLint/Prettier indent conflict by disabling ESLint indent rule (Prettier is formatting authority)"
annotations:
headlamp/plugin/archive-url: "https://github.com/privilegedescalation/headlamp-intel-gpu-plugin/releases/download/v0.4.0/intel-gpu-0.4.0.tar.gz"
headlamp/plugin/archive-checksum: sha256:f529794d7995b35b954fa32c10874fa8367f6f5cd8040600e47a3013373219df
headlamp/plugin/archive-url: "https://github.com/privilegedescalation/headlamp-intel-gpu-plugin/releases/download/v0.4.1/intel-gpu-0.4.1.tar.gz"
headlamp/plugin/archive-checksum: ""
headlamp/plugin/version-compat: ">=0.20.0"
headlamp/plugin/distro-compat: "in-cluster,web,app"
+1 -1
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@@ -1,6 +1,6 @@
{
"name": "intel-gpu",
"version": "0.4.0",
"version": "0.4.1",
"description": "Headlamp plugin for Intel GPU device plugin visibility and monitoring",
"repository": {
"type": "git",
+14 -9
View File
@@ -65,6 +65,18 @@ export function useIntelGpuContext(): IntelGpuContextValue {
return ctx;
}
// ---------------------------------------------------------------------------
// Helpers
// ---------------------------------------------------------------------------
/** Extract raw Kubernetes JSON from Headlamp KubeObject wrappers. */
const extractJsonData = (items: unknown[]): unknown[] =>
items.map(item =>
item && typeof item === 'object' && 'jsonData' in item
? (item as { jsonData: unknown }).jsonData
: item
);
// ---------------------------------------------------------------------------
// Provider
// ---------------------------------------------------------------------------
@@ -129,8 +141,8 @@ export function IntelGpuDataProvider({ children }: { children: React.ReactNode }
try {
const list = await ApiProxy.request(url);
if (!cancelled && isKubeList(list)) {
const gpuPluinPods = filterIntelGpuPluginPods(list.items);
foundPluginPods.push(...gpuPluinPods);
const gpuPluginPods = filterIntelGpuPluginPods(list.items);
foundPluginPods.push(...gpuPluginPods);
}
} catch {
// Silently ignore — some selectors may not match
@@ -170,13 +182,6 @@ export function IntelGpuDataProvider({ children }: { children: React.ReactNode }
// type helpers work correctly.
// ---------------------------------------------------------------------------
const extractJsonData = (items: unknown[]): unknown[] =>
items.map(item =>
item && typeof item === 'object' && 'jsonData' in item
? (item as { jsonData: unknown }).jsonData
: item
);
const gpuNodes = useMemo(() => {
if (!allNodes) return [];
return filterIntelGpuNodes(extractJsonData(allNodes as unknown[]));
-46
View File
@@ -1,46 +0,0 @@
/**
* AppBarGpuBadge — compact Intel GPU health indicator in the Headlamp app bar.
*
* Shows a status chip in the top navigation bar summarising GPU plugin health.
* Hides itself when no Intel GPU plugin is detected.
*/
import { StatusLabel } from '@kinvolk/headlamp-plugin/lib/CommonComponents';
import React from 'react';
import { useIntelGpuContext } from '../api/IntelGpuDataContext';
export default function AppBarGpuBadge() {
const { pluginInstalled, gpuNodes, devicePlugins, loading } = useIntelGpuContext();
// Hide when loading or no plugin present
if (loading || !pluginInstalled) return null;
const hasUnhealthyPlugin = devicePlugins.some(p => {
const desired = p.status?.desiredNumberScheduled ?? 0;
const ready = p.status?.numberReady ?? 0;
const unavailable = p.status?.numberUnavailable ?? 0;
return (desired > 0 && ready < desired) || unavailable > 0;
});
const status = hasUnhealthyPlugin ? 'warning' : 'success';
const nodeCount = gpuNodes.length;
return (
<div
style={{
display: 'flex',
alignItems: 'center',
gap: '4px',
padding: '0 8px',
cursor: 'default',
}}
title={`Intel GPU: ${nodeCount} node${nodeCount !== 1 ? 's' : ''}`}
>
<StatusLabel status={status}>
<span style={{ fontSize: '11px', fontWeight: 600 }}>
Intel GPU{nodeCount > 0 ? ` · ${nodeCount}N` : ''}
</span>
</StatusLabel>
</div>
);
}
+31 -20
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@@ -194,30 +194,41 @@ export default function MetricsPage() {
const [metrics, setMetrics] = useState<GpuMetrics | null>(null);
const [fetchError, setFetchError] = useState<string | null>(null);
const [fetching, setFetching] = useState(false);
const [fetchSeq, setFetchSeq] = useState(0);
const doFetch = useCallback(async () => {
setFetching(true);
setFetchError(null);
try {
const result = await fetchGpuMetrics();
setMetrics(result);
if (!result) {
setFetchError(
'Could not reach Prometheus. Ensure kube-prometheus-stack is installed in the monitoring namespace.'
);
}
} catch (e: unknown) {
setFetchError(e instanceof Error ? e.message : String(e));
} finally {
setFetching(false);
}
const doFetch = useCallback(() => {
setFetchSeq(s => s + 1);
}, []);
useEffect(() => {
if (!ctxLoading) {
void doFetch();
}
}, [ctxLoading, doFetch]);
if (ctxLoading) return;
let cancelled = false;
setFetching(true);
setFetchError(null);
fetchGpuMetrics()
.then(result => {
if (cancelled) return;
setMetrics(result);
if (!result) {
setFetchError(
'Could not reach Prometheus. Ensure kube-prometheus-stack is installed in the monitoring namespace.'
);
}
})
.catch((e: unknown) => {
if (cancelled) return;
setFetchError(e instanceof Error ? e.message : String(e));
})
.finally(() => {
if (!cancelled) setFetching(false);
});
return () => {
cancelled = true;
};
}, [ctxLoading, fetchSeq]);
if (ctxLoading) {
return <Loader title="Loading Intel GPU data..." />;
+4 -4
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@@ -52,11 +52,11 @@ export default function NodeDetailSection({ resource }: NodeDetailSectionProps)
metadata: { name: string; labels?: Record<string, string> };
};
const nodeName = (node as { metadata: { name: string } }).metadata.name;
const capacity = getGpuResources((node as any).status?.capacity);
const allocatable = getGpuResources((node as any).status?.allocatable);
const nodeName = node.metadata.name;
const capacity = getGpuResources(node.status?.capacity);
const allocatable = getGpuResources(node.status?.allocatable);
const gpuType = getNodeGpuType(node as any);
const gpuType = getNodeGpuType(node);
// Find GPU pods scheduled on this node
const podsOnNode = loading ? [] : gpuPods.filter(p => p.spec?.nodeName === nodeName);